In the practice of digital color image processing, an original color image, such as a photographic negative, is sampled periodically in three colors (e.g. red, green and blue) to produce a digital representation of the original color image. The digital color image is processed by applying digital image processing functions to improve such image qualities as sharpness, tone-scale, and color balance. The processed digital color image is then displayed on a display medium such as photographic film or paper.
FIG. 3 is a schematic diagram illustrating apparatus for digital image processing. Such apparatus includes an input device 1 for sampling the original color image in each of three colors, and analog-to-digital converters 2 for producing the digital color image in the three colors. Commonly employed input devices include drum and flat bed scanners, linear and area solid state image sensing arrays, and CRT and laser flying spot scanners, each being provided with appropriate color filters to produce the color separations.
Each digital color separation image is stored in a mass storage memory 3, such as a solid state memory frame-buffer, magnetic tape or disc storage device. A digital computer 4 applies the various image processing functions to the digital color image to produce the processed digital color image.
The digital computer 4 may comprise a main frame general purpose digital computer, or for higher speed operation, a digital computer specially configured for high speed digital processing of color images.
The processed digital color image is converted to sampled analog form by digital-to-analog converters 5 and is displayed on an output device 6 such as a drum or flat bed graphic arts scanner, or a CRT or laser flying spot scanner. The elements of the image reproduction apparatus communicate via a data and control bus 7.
As noted above, among the processing functions performed by the digital computer are the improvement of the tone-scale and color balance of the color image. In the article entitled "Tone Correction of Color Picture by Histogram Modification" by Yoichi Miyake, Nippon Shashin Sakkaishi, V. 48(2), pp. 94-101, 1980, the author proposes a digital color image processing method wherein the tone-scale corrections are effected by modifying the histogram of color values of the green separation image. Color corrections are implemented by solving a conventional set of color masking equations of the form: EQU R'=a.sub.11 R+a.sub.12 G+a.sub.13 B (1) EQU G'=a.sub.21 R+a.sub.22 G+a.sub.23 B (2) EQU B'=a.sub.31 R+a.sub.32 G+a.sub.33 B (3)
where the matrix of color correction coefficients a.sub.ij are determined primarily by the characteristics of the input and output media.
An improvement to this process wherein both tone scale and color balance are corrected using histogram modification techniques is disclosed in copending U.S. patent application Ser. No. 730,627 filed May 6, 1985, by Alkofer.
According to the digital color image processing method of Alkofer, a Laplacian filter is applied to each of the color components of the image to detect local contrast. The color values are divided into contrast intervals, and one of the contrast intervals is selected based on the similarity of the histograms of color values in the selected contrast interval. The histograms of color values in the selected contrast interval are normallized to produce color reproduction functions, and the color reproduction functions are applied to the color components of the digital color image.
The method of Alkofer is based upon two principle observations regarding the statistical properties of the color values in a high quality color image. The first of these principles is that a truly random sample of color values (e.g. photographic density or log radiance) in a high quality color image will form a normal (Gaussian) distribution. The second principle is that the standard deviation of a random sample of color values is invariant with respect to wavelength (i.e. color). A truly random sample of color values of one color will have the same standard deviation as a truly random sample of another color.
The first principle noted above implies that a function that normalizes a random sample of color values will serve well as a color reproduction function, assuming that any deviation from normality in the random sample was caused by some "problem" with the original. The first principle combined with the second principle noted above implies that color values in all three colors having an equal distance in their number of standard deviations from the means of their respective color distributions should always combine to produce a neutral (i.e. gray).
The degree of success (i.e. the appropriateness of the color corrections) achievable by this method is a strong function of the randomness of the sample of color values used to generate the color reproduction functions. Alkofer relied upon the selection of color values from the contrast interval based upon the similarities of the histograms of color values in the contrast interval, to insure the desired randomness in selection of color values from the image. While Alkofer's method represents a subtantial improvement over the prior art, there is still observed to be some situations in which the "randomness" in selecting color values is perturbed by large areas where film grain noise predominates in an image (such as blue sky, causing a subtle yellow shift in the processed image) or areas of fine texture (such as grass or foilage, causing a subtle magenta shift in the processed image).
It is the object of the present invention to provide an improved color digital image processing method, and in particular to provide an improved method for sampling the color values in a color image for use in normalizing the sample of color values to produce color reproduction functions.